There has been a tremendous interest in Jupyter and related open source technologies in the data science community. While some companies have started using Jupyter internally or are working with vendors that have started incorporating Jupyter in their product offering to help data scientist teams scale in enterprise settings, it is not always clear how Jupyter fits in the larger data and analytics ecosystem of most large enterprises.
Gerald Rouselle reviews some of the trends in modern data and analytics ecosystems for large enterprises and shares some of the key challenges and opportunities for Jupyter adoption. He also details some recent examples and experiments in incorporating Jupyter in commercial products and platforms.
Gerald Rousselle is director of product management at Teradata.
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